Publications
Collective design of robot locomotion
ALIFE, 14, 138-145, 2014
Status: Published
Citations:
Cite: [bibtex]

Abstract: It has been shown that the collective action of non-experts
can compete favorably with an individual expert or an optimization
method on a given problem. However, the best
method for organizing collective problem solving is still an
open question. Using the domain of robotics, we examine
whether cooperative search for design strategies is superior
to individual search. We use a web-based robot simulation to
determine whether groups of human users can leverage design
intuition from others to focus search on relevant parts of
a complex design space. We show that individuals that work
cooperatively with the aid of a simple optimization algorithm
are better able to improve the design of robot locomotion than
if they were to work individually with the aid of the optimization
algorithm. This result suggests that groups of designers
may more effectively work in tandem with optimization algorithms
than individuals working in isolation.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Continuous Self-Modeling. Science 314, 1118 (2006). [Journal Page]

Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.

Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.

Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.

Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).